陈小龙, 贾文菡, 陈科其, 梁晨露, 狄乾斌. 中国淡水养殖碳排放效率的空间关联网络结构及其影响因素[J]. 中国生态农业学报 (中英文), 2024, 32(7): 1122−1135. DOI: 10.12357/cjea.20230468
引用本文: 陈小龙, 贾文菡, 陈科其, 梁晨露, 狄乾斌. 中国淡水养殖碳排放效率的空间关联网络结构及其影响因素[J]. 中国生态农业学报 (中英文), 2024, 32(7): 1122−1135. DOI: 10.12357/cjea.20230468
CHEN X L, JIA W H, CHEN K Q, LIANG C L, DI Q B. Spatial correlation network structure and influencing factors of carbon emission efficiency of freshwater aquaculture in China[J]. Chinese Journal of Eco-Agriculture, 2024, 32(7): 1122−1135. DOI: 10.12357/cjea.20230468
Citation: CHEN X L, JIA W H, CHEN K Q, LIANG C L, DI Q B. Spatial correlation network structure and influencing factors of carbon emission efficiency of freshwater aquaculture in China[J]. Chinese Journal of Eco-Agriculture, 2024, 32(7): 1122−1135. DOI: 10.12357/cjea.20230468

中国淡水养殖碳排放效率的空间关联网络结构及其影响因素

Spatial correlation network structure and influencing factors of carbon emission efficiency of freshwater aquaculture in China

  • 摘要: 推进绿色生态养殖, 科学把握淡水养殖碳排放效率的空间关联网络结构, 不仅是水产行业可持续发展的客观要求, 更是农业低碳转型发展的重要基础。为制定更科学的养殖方案, 提高资源利用效率, 减少对环境的破坏, 本研究从空间关联视角研究中国淡水养殖碳排放效率, 以2008—2021年中国30个省市为研究对象, 运用Super-SBM模型测度淡水养殖碳排放效率, 利用修正的引力模型和社会网络分析法分析其空间关联网络结构特征, 二次指派程序(QAP)模型实证分析其影响因素。结果表明: ①中国淡水养殖碳排放效率时空分布不均衡, 时间上呈波动上升态势, 空间上区域间差距不断缩小。②空间联系强度逐渐增强, 但距理想状态仍有差距; 整体网络关联性也不断增强, 结构较为稳定。③东部沿海地区在空间网络中始终处于主导地位, 对碳排放效率空间关联影响显著, 西北、西南和东北地区在网络中处于被支配地位, 对碳排放效率空间关联性的影响较弱, 中部地区部分省市发挥“桥梁”与“中介”作用。④养殖品种结构优化、淡水养殖技术提高均可促进养殖区域间合作交流, 促进空间关联网络形成; 碳汇对生态保护和治理具有重要意义, 基础设施建设改善了区域交通和通信条件, 使地区间联系更紧密, 推动空间关联网络形成; 养殖密度的增加导致养殖环境的恶化, 不利于产业可持续发展; 渔业经济发展对空间关联网络的形成产生正向影响, 但不显著。为发展绿色低碳养殖, 提升淡水养殖碳排放效率, 应因地制宜地制定区域协同发展政策、优化养殖品种结构和提升养殖技术; 同时重视不同省份间的低碳减排资源, 推动淡水养殖碳排放效率区域联动; 利用养殖密度相似性, 调动区域同化效应, 进一步缩小地区间差距。

     

    Abstract: The objectives of the sustainable development of the aquaculture industry involve promoting green ecological aquaculture, scientifically grasping the spatial correlation network structure of freshwater aquaculture carbon emission efficiency, and laying the foundation for the development of low-carbon transformation of agriculture. To develop a more scientific aquaculture program, improve the efficiency of resource use, and reduce damage to the environment, this study investigated the carbon emission efficiency of freshwater aquaculture in China from a spatial correlation perspective, taking 30 provinces and cities in China as the research object from 2008 to 2021, measured the carbon emission efficiency of freshwater aquaculture using the Super-Slacks Based Measurement (SBM) model, analyzed the characteristics of its spatial correlation network structure on the basis of the modified gravitational model and social network analysis, and analyzed the influencing factors empirically using the Quadratic Assignment Procedure model. The results showed that the spatial and temporal distribution of the carbon emission efficiency of freshwater aquaculture in China was uneven, with a fluctuating upward trend over time and a decreasing gap between regions in space. The strength of the spatial linkage gradually increased, but it was still far from the ideal state; the overall network correlation also increased, and the structure was relatively stable. The eastern coastal region has always been in a dominant position in the spatial network and has a significant impact on the spatial correlation of carbon emission efficiency, while the northwestern, southwestern and northeastern regions are in a subordinate position in the network and have a weak impact on the spatial correlation of carbon emission efficiency, and some provinces and municipalities in the central region play the roles of “bridges” and “intermediaries”. The optimization of aquaculture species structure and the improvement of freshwater aquaculture technology can promote cooperation and exchange between aquaculture regions and facilitate the formation of spatial linkage networks. Carbon sinks are important for ecological protection and governance, and the construction of infrastructure improves the conditions of regional transportation and communication, which makes the inter-regional links convenient and close and promotes the formation of spatial linkage networks. The increase in aquaculture density will lead to the deterioration of the aquaculture environment, which is not conducive to the sustainable development of the industry, and the economic development of the fishery industry has a positive but insignificant impact on the formation of spatial connectivity networks. To develop green and low-carbon aquaculture and enhance the carbon emission efficiency of freshwater aquaculture, regional synergistic development policies, optimization of the structure of aquaculture species, and upgradation of aquaculture technology should be formulated according to local conditions. Emphasis should be placed on low-carbon emission reduction resources between different provinces, regional linkages in carbon emission efficiency of freshwater aquaculture should be promoted, and similarities in aquaculture densities should be used to mobilize regional assimilation effects and further narrow the gap between regions.

     

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